Date of Award
Fall 12-2013
Degree Type
Honors College Thesis
Department
Computing
First Advisor
Shaoen Wu
Advisor Department
Computing
Abstract
Cloud computing is a “new frontier” in the world of computing. One of the cloud architectures widely used is the Hadoop running environment. Hadoop consists of many parts—including MapReduce, TaskTrackers, and JobTrackers. Right now, there is no fault-tolerance for JobTrackers in Hadoop. This paper analyzes four different distributed hash algorithms (Pastry, Tapestry, CAN, and Chord) that could be implemented inside Hadoop to improve JobTracker fault-tolerance. We recommend Chord as the best suited for integration and improvement of Hadoop.
Copyright
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Recommended Citation
Knaus, Benjamin R., "An Analysis of Peer-to-Peer Distributed Hash Algorithms in Improving Fault Tolerance in the Hadoop Running Environment" (2013). Honors Theses. 195.
https://aquila.usm.edu/honors_theses/195